Cloud physics, lack of data hurt efforts to pinpoint deadly downpours

Published 5:30 am, Sunday, September 16, 2007

The lumbering storm would drop 5 to 10 inches of rain across much of the area, with isolated totals of 15 inches, forecasters said Wednesday afternoon. The storm turned, and only extreme southeast Harris County got rain — four-hundredths of an inch.

Even locations directly in Humberto's path, such as Beaumont and Lake Charles, La., received only 2 to 3 inches of rain.

The experience came a month after Tropical Storm Erin surprised Houston. Forecasters predicted the storm's biggest impact would come near its point of landfall just north of Rockport — not 200 miles up the coast in Houston. Then came the deluge, with Erin dropping nearly 10 inches of rain on parts of Harris County.

The two tropical systems highlight the challenge of predicting the wheres and whens of severe rainfall.

Such forecasts are especially difficult in Gulf Coast communities, where the atmosphere has access to ample moisture both from hurricanes and the bathwater-warm Gulf.

The fact that Harris County is essentially a tabletop only heightens the importance of rainfall forecasting. (To approximate the area's slope toward Galveston Bay, imagine a pool table and put a quarter under the legs at one end.) When severe rain falls, it pools.

"Getting severe rainfall right is always one of our biggest challenges," said Lance Wood, science operations officer for the Houston/Galveston office of the National Weather Service. "And we don't always get it right."

The problem is rooted in the physics of thunderstorms. The heaviest thunderstorm cells typically are localized events, especially near warm oceans.

"In Houston, it can be pouring down rain on one side of the street, and be completely dry on the other," said Suzanne Van Cooten, a researcher at the National Severe Storms Laboratory based in Norman, Okla.

Deadly flooding

Consider the most widespread flooding event in Houston during the past year — the torrential rains of Oct. 16, when a woman and her teenage daughter died in their submerged sport-utility vehicle. At one gauge in Clear Lake that day, 11 inches of rain fell. At another a few miles away, the total was just 4 inches.

Forecasters rely largely on computer models.

"Models are good at telling us where the conditions are ripe for thunderstorms," said Bernard Meisner, the Fort Worth-based chief of science and training for the Southern Region of the National Weather Service. "But they're of little use in picking out where everything will come together in the atmosphere just right, or where a thunderstorm will stall and you'll get flooding."

The uncertainty was evident last October, when exceptionally high levels of moisture saturated the atmosphere along the southeast Texas and central Louisiana coasts. With daytime heating on the 16th, forecasters expected storms.

The 24-hour precipitation forecast by one model, the GFS, which is regularly used by experts, accurately predicted severe rainfall. But it placed the heaviest rain over central Louisiana, well east of Houston. The greater Houston area, the model indicated, would get only an inch or so of rain.

A few models accurately showed the strongest weather over Texas, but most favored Louisiana. Tasked with picking the "correct" model, experts generally follow the most commonly offered forecast.

Lack of data

Model results vary widely, because scientists don't yet understand all the physical processes that occur within clouds to generate severe rain. The problem is compounded by a lack of crucial data about conditions above Earth's surface, such as the atmosphere's moisture content one mile up.

As a result, models must do with best guesses and assumptions and gloss over details. They then try to predict how conditions will change.

It's like the children's game of telephone, in which an early mistake often results in a large, error at the end of the exercise.

So, too, it is with models, only on a larger scale. The models begin with millions of data points and assumptions, then repeat the process many times. Initial errors rapidly multiply, and severe rain falls over Houston instead of Louisiana.

Even if forecasters had correctly placed Houston as the primary rainfall target on Oct. 16, they would have been unable to pinpoint which part of the city would get hit hardest.

Models generate data by grid points, giving predicted temperatures, air pressures and so forth for one spot on a map. Some models do that for a point every 25 miles, others for points as little as eight miles apart.

Since thunderstorm cells are much smaller than that, the models can't pick out small but crucial details such as boundaries between frontal systems and cool air streaming from a thunderstorm complex, where the heaviest rain falls.

To address the deficiencies in rainfall forecasting, scientists have taken several tacks.

One is employing ever more powerful supercomputers to crunch through galaxies of data. The American Meteorological Society says the accuracy of short- and long-term U.S. forecasts has roughly doubled in the past decade. For rainfall, 48-hour precipitation forecasts are now as accurate as 24-hour predictions a decade ago.

But scientists must increase their knowledge of cloud physics to improve model equations, Meisner said. That is happening, thanks to government planes that fly into thunderstorms much as hurricane hunters do in tropical systems.

More improvement should come through collecting more data at the Earth's surface and higher in the atmosphere. Better data lead to fewer assumptions in models and, therefore, more accurate information at the end of their runs.

Airplanes and sensors

Airplanes have long carried sensors to measure wind speeds with the aim of maximizing tail winds. Airlines, which rely heavily on weather forecasts, realized about two decades ago that they would benefit by sharing this data with computer modelers.

Perhaps most importantly, a private, North Carolina-based company named AirDat is working to attach humidity sensors to aircraft. Data about moisture content in the atmosphere — a key indicator of thunderstorm potential — could improve precipitation forecasts.

Flooding experts are doing what they can to help emergency planners. At Rice University, Phil Bedient has led the development of computer models that take real-time rainfall data and information about bayous, watersheds and detention ponds to predict how soon a certain part of Houston will flood.

Bedient said the system now can give three to six hours of lead time, enough to allow the evacuation of crucial facilities or the rerouting of emergency vehicles.

"Our aim right now is to help people make real-time decisions once the rain begins falling," Bedient said.